{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a supplementary file for the tutorial this week and can be safely ignored\n",
    "solutions will also be posted for this at the end of the week if you are interested\n",
    "if you find any errors please notify me at omarghattas1991@gmail.com"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Aim: We are going to explore three fundamental algorithms that are the basis for deep learning:\n",
    "1. the Perceptron training rule\n",
    "2. Gradient Descent\n",
    "3. Stochastic Gradient Descent\n",
    "\n",
    "At the end of this lab you should be comfortable with perceptron training and the basics of \n",
    "gradient descent -> be able to start thinking about neural networks and building them from scratch \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "np.random.seed(43)\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Helper Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_scatter(X, y, w):\n",
    "    pos_points = X[np.where(y==1)[0]]\n",
    "    neg_points = X[np.where(y==-1)[0]]\n",
    "    plt.scatter(pos_points[:, 1], pos_points[:, 2], color='blue')\n",
    "    plt.scatter(neg_points[:, 1], neg_points[:, 2], color='red')\n",
    "    xx = np.linspace(-6,6)\n",
    "    yy = -w[0]/w[2] - w[1]/w[2] * xx\n",
    "    plt.plot(xx, yy, color='orange')\n",
    "    \n",
    "    ratio = (w[2]/w[1] + w[1]/w[2])\n",
    "    xpt = (-1*w[0] / w[2]) * 1/ratio\n",
    "    ypt = (-1*w[0] / w[1]) * 1/ratio\n",
    "    \n",
    "    plt.axes().arrow(xpt, ypt, w[1], w[2], head_width=0.2, color='orange')\n",
    "    plt.axis('equal')\n",
    "    plt.show()\n",
    "    \n",
    "#plot_scatter(X, y, w=np.array([0,-1,3]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Applications/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: RuntimeWarning: covariance is not symmetric positive-semidefinite.\n",
      "  \n",
      "/Applications/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:3: RuntimeWarning: covariance is not symmetric positive-semidefinite.\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "def generate_data(n=20):\n",
    "    dist_01 = np.random.multivariate_normal(np.array([2,2]), np.array([[1,0.9],[0.5,1]]), n)\n",
    "    dist_02 = np.random.multivariate_normal(np.array([-2,-2]),np.array([[1,0],[0.3,1]]), n)\n",
    "    X = np.concatenate((np.ones(2*n).reshape(-1,1), np.concatenate((dist_01, dist_02))), axis=1)\n",
    "    y = np.concatenate((np.ones(n), -1*np.ones(n)))\n",
    "    shuffle_idx = np.random.choice(2*n, size=2*n, replace=False)\n",
    "    X = X[shuffle_idx]\n",
    "    y = y[shuffle_idx]\n",
    "    return X, y\n",
    "X, y = generate_data()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Perceptron Training Rule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def train_perceptron(X, y, eta=1):\n",
    "    w = np.array([-2,-1,3])\n",
    "    nmb_data = X.shape[0]\n",
    "    '''\n",
    "    your code here\n",
    "    '''\n",
    "    #iteratively train model, until there is no error, if there is an error, retrain the model\n",
    "    \n",
    "    while True:\n",
    "        count = 0\n",
    "        for i in range(nmb_data):\n",
    "            if(((y[i] * w.T) @ X[i]) <= 0):\n",
    "                w = w + eta * y[i] * X[i]\n",
    "                plot_scatter(X, y, w)\n",
    "                print(\"Iteration {0}, w is {1}\".format(count,w))\n",
    "                count = 0\n",
    "            count += 1\n",
    "            print(\"Iteration {0}, w is {1}\".format(count,w))\n",
    "            if(count == nmb_data):\n",
    "                print('converged and w is ',w)\n",
    "                plot_scatter(X, y, w)\n",
    "                return\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 1, w is [-2 -1  3]\n",
      "Iteration 2, w is [-2 -1  3]\n",
      "Iteration 3, w is [-2 -1  3]\n",
      "Iteration 4, w is [-2 -1  3]\n",
      "Iteration 5, w is [-2 -1  3]\n",
      "Iteration 6, w is [-2 -1  3]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Applications/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: RuntimeWarning: covariance is not symmetric positive-semidefinite.\n",
      "  \n",
      "/Applications/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:3: RuntimeWarning: covariance is not symmetric positive-semidefinite.\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 6, w is [-1.9        -0.81402     3.10919902]\n",
      "Iteration 1, w is [-1.9        -0.81402     3.10919902]\n",
      "Iteration 2, w is [-1.9        -0.81402     3.10919902]\n",
      "Iteration 3, w is [-1.9        -0.81402     3.10919902]\n",
      "Iteration 4, w is [-1.9        -0.81402     3.10919902]\n",
      "Iteration 5, w is [-1.9        -0.81402     3.10919902]\n",
      "Iteration 6, w is [-1.9        -0.81402     3.10919902]\n",
      "Iteration 7, w is [-1.9        -0.81402     3.10919902]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 7, w is [-1.8        -0.60490566  3.20777524]\n",
      "Iteration 1, w is [-1.8        -0.60490566  3.20777524]\n",
      "Iteration 2, w is [-1.8        -0.60490566  3.20777524]\n",
      "Iteration 3, w is [-1.8        -0.60490566  3.20777524]\n",
      "Iteration 4, w is [-1.8        -0.60490566  3.20777524]\n",
      "Iteration 5, w is [-1.8        -0.60490566  3.20777524]\n",
      "Iteration 6, w is [-1.8        -0.60490566  3.20777524]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 6, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 1, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 2, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 3, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 4, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 5, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 6, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 7, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 8, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 9, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 10, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 11, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 12, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 13, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 14, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 15, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 16, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 17, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 18, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 19, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 20, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 21, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 1, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 2, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 3, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 4, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 5, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 6, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 7, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 8, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 9, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 10, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 11, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 12, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 13, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 14, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 15, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 16, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 17, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 18, w is [-1.7        -0.48503645  3.17431807]\n",
      "Iteration 19, w is [-1.7        -0.48503645  3.17431807]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 1, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 2, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 3, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 4, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 5, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 6, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 7, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 8, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 9, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 10, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 11, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 12, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 13, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 14, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 15, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 16, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 17, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 18, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 19, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 20, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 21, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 1, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 2, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 3, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 4, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 5, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 6, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 7, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 8, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 9, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 10, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 11, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 12, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 13, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 14, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 15, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 16, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 17, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 18, w is [-1.6        -0.36516723  3.1408609 ]\n",
      "Iteration 19, w is [-1.6        -0.36516723  3.1408609 ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 1, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 2, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 3, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 4, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 5, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 6, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 7, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 8, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 9, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 10, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 11, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 12, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 13, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 14, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 15, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 16, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 17, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 18, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 19, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 20, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 21, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 1, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 2, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 3, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 4, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 5, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 6, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 7, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 8, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 9, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 10, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 11, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 12, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 13, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 14, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 15, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 16, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 17, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 18, w is [-1.5        -0.24529802  3.10740374]\n",
      "Iteration 19, w is [-1.5        -0.24529802  3.10740374]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 1, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 2, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 3, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 4, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 5, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 6, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 7, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 8, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 9, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 10, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 11, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 12, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 13, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 14, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 15, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 16, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 17, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 18, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 19, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 20, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 21, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 1, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 2, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 3, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 4, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 5, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 6, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 7, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 8, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 9, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 10, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 11, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 12, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 13, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 14, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 15, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 16, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 17, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 18, w is [-1.4        -0.12542881  3.07394657]\n",
      "Iteration 19, w is [-1.4        -0.12542881  3.07394657]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 1, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 2, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 3, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 4, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 5, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 6, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 7, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 8, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 9, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 10, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 11, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 12, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 13, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 14, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 15, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 16, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 17, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 18, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 19, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 20, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 21, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 1, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 2, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 3, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 4, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 5, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 6, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 7, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 8, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 9, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 10, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 11, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 12, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 13, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 14, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 15, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 16, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 17, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 18, w is [-1.3        -0.00555959  3.0404894 ]\n",
      "Iteration 19, w is [-1.3        -0.00555959  3.0404894 ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 1, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 2, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 3, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 4, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 5, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 6, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 7, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 8, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 9, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 10, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 11, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 12, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 13, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 14, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 15, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 16, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 17, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 18, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 19, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 20, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 21, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 1, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 2, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 3, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 4, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 5, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 6, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 7, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 8, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 9, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 10, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 11, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 12, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 13, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 14, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 15, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 16, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 17, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 18, w is [-1.2         0.11430962  3.00703223]\n",
      "Iteration 19, w is [-1.2         0.11430962  3.00703223]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 1, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 2, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 3, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 4, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 5, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 6, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 7, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 8, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 9, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 10, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 11, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 12, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 13, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 14, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 15, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 16, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 17, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 18, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 19, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 20, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 21, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 1, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 2, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 3, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 4, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 5, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 6, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 7, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 8, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 9, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 10, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 11, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 12, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 13, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 14, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 15, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 16, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 17, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 18, w is [-1.1         0.23417883  2.97357506]\n",
      "Iteration 19, w is [-1.1         0.23417883  2.97357506]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 1, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 2, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 3, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 4, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 5, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 6, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 7, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 8, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 9, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 10, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 11, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 12, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 13, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 14, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 15, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 16, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 17, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 18, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 19, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 20, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 21, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 1, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 2, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 3, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 4, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 5, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 6, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 7, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 8, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 9, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 10, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 11, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 12, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 13, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 14, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 15, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 16, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 17, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 18, w is [-1.          0.35404804  2.94011789]\n",
      "Iteration 19, w is [-1.          0.35404804  2.94011789]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 1, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 2, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 3, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 4, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 5, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 6, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 7, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 8, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 9, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 10, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 11, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 12, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 13, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 14, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 15, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 16, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 17, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 18, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 19, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 20, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 21, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 1, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 2, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 3, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 4, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 5, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 6, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 7, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 8, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 9, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 10, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 11, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 12, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 13, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 14, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 15, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 16, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 17, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 18, w is [-0.9         0.47391726  2.90666072]\n",
      "Iteration 19, w is [-0.9         0.47391726  2.90666072]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 1, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 2, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 3, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 4, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 5, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 6, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 7, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 8, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 9, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 10, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 11, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 12, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 13, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 14, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 15, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 16, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 17, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 18, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 19, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 20, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 21, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 1, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 2, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 3, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 4, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 5, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 6, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 7, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 8, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 9, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 10, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 11, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 12, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 13, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 14, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 15, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 16, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 17, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 18, w is [-0.8         0.59378647  2.87320355]\n",
      "Iteration 19, w is [-0.8         0.59378647  2.87320355]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 1, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 2, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 3, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 4, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 5, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 6, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 7, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 8, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 9, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 10, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 11, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 12, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 13, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 14, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 15, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 16, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 17, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 18, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 19, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 20, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 21, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 1, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 2, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 3, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 4, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 5, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 6, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 7, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 8, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 9, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 10, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 11, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 12, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 13, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 14, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 15, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 16, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 17, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 18, w is [-0.7         0.71365568  2.83974639]\n",
      "Iteration 19, w is [-0.7         0.71365568  2.83974639]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 1, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 2, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 3, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 4, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 5, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 6, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 7, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 8, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 9, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 10, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 11, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 12, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 13, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 14, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 15, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 16, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 17, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 18, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 19, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 20, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 21, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 1, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 2, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 3, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 4, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 5, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 6, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 7, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 8, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 9, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 10, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 11, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 12, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 13, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 14, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 15, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 16, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 17, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 18, w is [-0.6         0.8335249   2.80628922]\n",
      "Iteration 19, w is [-0.6         0.8335249   2.80628922]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 1, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 2, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 3, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 4, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 5, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 6, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 7, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 8, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 9, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 10, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 11, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 12, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 13, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 14, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 15, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 16, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 17, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 18, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 19, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 20, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 21, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 1, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 2, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 3, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 4, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 5, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 6, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 7, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 8, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 9, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 10, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 11, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 12, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 13, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 14, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 15, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 16, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 17, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 18, w is [-0.5         0.95339411  2.77283205]\n",
      "Iteration 19, w is [-0.5         0.95339411  2.77283205]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 1, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 2, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 3, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 4, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 5, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 6, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 7, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 8, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 9, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 10, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 11, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 12, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 13, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 14, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 15, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 16, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 17, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 18, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 19, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 20, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 21, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 1, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 2, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 3, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 4, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 5, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 6, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 7, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 8, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 9, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 10, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 11, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 12, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 13, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 14, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 15, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 16, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 17, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 18, w is [-0.4         1.07326332  2.73937488]\n",
      "Iteration 19, w is [-0.4         1.07326332  2.73937488]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 19, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 1, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 2, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 3, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 4, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 5, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 6, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 7, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 8, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 9, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 10, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 11, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 12, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 13, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 14, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 15, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 16, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 17, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 18, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 19, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 20, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 21, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 1, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 2, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 3, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 4, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 5, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 6, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 7, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 8, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 9, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 10, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 11, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 12, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 13, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 14, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 15, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 16, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 17, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 18, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 19, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 20, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 21, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 22, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 23, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 24, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 25, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 26, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 27, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 28, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 29, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 30, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 31, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 32, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 33, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 34, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 35, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 36, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 37, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 38, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 39, w is [-0.3         1.19313254  2.70591771]\n",
      "Iteration 40, w is [-0.3         1.19313254  2.70591771]\n",
      "converged and w is  [-0.3         1.19313254  2.70591771]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, y = generate_data()\n",
    "train_perceptron(X, y, eta=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gradient Descent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sigmoid(x,a=1):\n",
    "    # your code here\n",
    "    return 1/(1+np.exp(-a*x))\n",
    "\n",
    "def grad_sigmoid(x, a=1):\n",
    "    # your code here\n",
    "    return sigmoid(x,a)*(1-sigmoid(x,a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot sig functions \n",
    "xx = np.linspace(-6,6,1000)\n",
    "a_vals = [0.4,1,2,3]\n",
    "cols = ['red', 'blue', 'orange', 'green']\n",
    "y_sig = [sigmoid(xx, a_val) for a_val in a_vals]\n",
    "y_grad_sig = [grad_sigmoid(xx, a_val) for a_val in a_vals]\n",
    "\n",
    "for i in range(len(a_vals)):\n",
    "    label = str(a_vals[i])\n",
    "    plt.plot(xx, y_sig[i], label=rf'$a={label}$', color=cols[i])\n",
    "    plt.plot(xx, y_grad_sig[i], color=cols[i])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "def loss_i(w, x_i, y_i):\n",
    "    '''squared loss for i-th data point'''\n",
    "    # your code here\n",
    "    return (y_i - sigmoid(x_i))**2\n",
    "    \n",
    "    \n",
    "def grad_loss_i(w, x_i, y_i):\n",
    "    '''grad loss for i-th data point'''\n",
    "    # your code here\n",
    "    return (y_i - sigmoid(x_i)) * (-x_i) * grad_sigmoid(w@x_i)\n",
    "\n",
    "def gradient_descent(X, y, eta, T):\n",
    "    #T iterations\n",
    "    nmb_data = X.shape[0]\n",
    "    w = np.array([-2,-1,-3])\n",
    "    plot_scatter(X, y, w)\n",
    "    # your code here\n",
    "    for t in range(T):\n",
    "        loss = 0\n",
    "        grad_loss = 0\n",
    "        for i in range(nmb_data):\n",
    "            loss += loss_i(w,X[i],y[i])\n",
    "            grad_loss += grad_loss_i(w,X[i],y[i])\n",
    "        loss *= 0.5\n",
    "        w = w-eta*grad_loss\n",
    "        plot_scatter(X, y, w)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Applications/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: RuntimeWarning: covariance is not symmetric positive-semidefinite.\n",
      "  \n",
      "/Applications/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:3: RuntimeWarning: covariance is not symmetric positive-semidefinite.\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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KOfmFUS92ncfLu87i0Rcu4+sP/9GIYd/QAN/4RvQli4xH3IHfDOzMet8VLhMpDUMhbwY33/yr+RM6O+F3fgdmzeK7i9uZPHmkHRirOzJcfO4TzJiS+24mNTVw993qxpHkxR34uW4NccIUg2a23Mw6zKyjt7c35nKk6mW34mfN+lXIQxD0w/X1ceE9y1m/rJ35I4y8vPfZNupqB7juggdyrh8cVNhLaYg78LuAVNb7FmBX9gbuvsrd0+6ebmxsjLkcqTrDA37Zsl+14vv6cof8cP39XLhuBdu3B5u7c0L4b3z9Q3TubaXtw9HMrSMSl7gDfwNwppmdbmYNwI3A2piPKRIYPs1lX1/uy2bHYtiVVytXktXNY6zekOGKDzzC1IkH3vPRmTPzO6RI1GINfHc/BtwKrAe2AD9w9xfjPKbIccOnuSzEsAl1broJVq0KWvpm8NOdGSY2HOb69LoTttOXtVJKYr/S1t3XuftZ7v4+d9flJhKv7C6cXPMh5CvHXwY33RQMsxwchH//0W/AxNl85fdXH/8lMH++vqyV0qIrbaVyDHXhRNWqz1ZbG+x/pPSuqYWWpczf/l22bz0EdbphrZQezaUjlSPKLpzhBgbgd3/35DegTWXg2DvwxiPx1CBSIAW+VI647xV49CjcdtvI62d/Euqnw8418dYhkicFvlSOYtwrsK9v5HW1DdByPXSv1Z2rpCQp8KVynDhWMhmpDBx5E3b/ONk6RHJQ4EvlGD5WMtecxoUabVD93Cugbgrs1EVYUnoU+FJZssdKjuUq2vEYy6D6ukkwb3Fw28LBPC/yEomJAl9kLMYzqD7VBu/uhr0/i78ukXFQ4EvlKnROAzP47GeDvxS2bx/7FVTzFkNNg7p1pOQo8KVyFTKnwfz58C//At/+9vg/W39K0Je/c3X03UoiBVDgS+UqZE6DgweDqZOzboQyLq1t0L8D9m3MvwaRiCnwpbKNNIn9aIamTu7sDKZrGG/oN18HVhu08kVKhAJfKlsUY/P7+4NpG8ZjwkyYc3HQj69uHSkRCnypfJMimMgsn2kbUhk48Ars/2XhxxeJgAJfKtfQ7JnZ0yFMnhyMvBm6OKtmjP8F8pm2oeUGwNStIyVDgS+VK9fsmf39sG7dry7OmjFj9P3U1wddQ+M1qQkaf0PDM6VkKPClco3UDZO9fN++0fczbVr+I35aMvDWc3BgW36fF4lQbIFvZneYWbeZbQofi+M6lkhOI3XDZC8fS1fNWH4pjCSVCZ7VypcSEHcL/+vuvjB8rBt9c5EI5RqhM3nyid0zYxnFU8i0y1MXwIwLNEe+lAR16UjlGj575vz5wfvs7pnsbeC9M2wO/wWRj9Y26Hsa+rsL249IgeIO/FvN7Hkzu9vMxvDtmEjEsmfPHGk+nKFt3IPpFE72CyIfLUPdOmrlS7LMC7goxMweA+bmWLUCeBrYCzjwZaDJ3W/JsY/lwHKA1tbWD3V2duZdj0jJeug8mDAbLnsi6UqkApnZRndPj7ZdXSEHcffLxljMPwIPjrCPVcAqgHQ6rUsSpTK1ZOCXX4F3e2FiY9LVSJWKc5ROU9bbpcDmuI4lUvJSGfDB4H63IgmJsw//L83sBTN7HrgY+MMYjyVS2mYshCmnww4Nz5TkFNSlczLufnNc+xYpO2ZBK/+Vb8KR/dBwatIVSRXSsEyRYkm1weBR2PVQ0pVIlVLgixTLrI/ApHm66lYSo8AXKRargZalsOthONY/+vYiEVPgixRTKgMDh6Dnh0lXIlVIgS9STLMvCu6GpTnyJQEKfJFiqqmD5iXQ/QAMHE66GqkyCnyRYktl4OjbsPtHSVciVUaBL1Jscy+DulM0WkeKToEvUmy1E6D5Wui6HwaPJV2NVBEFvkgSUhk4vBd6n0q6EqkiCnyRJMy7GmonarSOFJUCXyQJdVOg6aog8H0w6WqkSijwRZKSaoND3dC3IelKpEoo8EWS0nwt1NRrtI4UjQJfJCkN02HOpWG3jm72JvFT4IskKZWBg9vgreeTrkSqgAJfJEktS4JZNDVaR4pAgS+SpImzofET6seXoigo8M3st8zsRTMbNLP0sHVfNLOtZvaymV1ZWJkiFSyVgf0vwtsvJ12JVLhCW/ibgQzwZPZCMzsXuBE4D7gK+LaZ1RZ4LJHKlMoEz+rWkZgVFPjuvsXdczVLlgDfd/fD7v46sBVYVMixRCrW5BaYuUiBL7GLqw+/GdiZ9b4rXCYiuaTaYF8HvLMj6Uqkgo0a+Gb2mJltzvFYcrKP5ViWc6CxmS03sw4z6+jt7R1r3SKVpWVp8KxWvsSobrQN3P2yPPbbBaSy3rcAu0bY/ypgFUA6ndbVJ1Kdpp0J0z8QjNY55wtJVyMVKq4unbXAjWY2wcxOB84Eno3pWCKVoSUDvf8Fh95IuhKpUIUOy1xqZl3Ax4CHzGw9gLu/CPwA+CXwQ+Dz7j5QaLEiFa21DfDgxigiMTAvoTk80um0d3R0JF2GSDLc4YGzYOoZcMn6pKuRMmJmG909Pdp2utJWpFSYBa383T+CI28mXY1UIAW+SClpyYAfg64Hkq5EKpACX6SUzEwHF2J1aXimRE+BL1JKrCZo5fesh6MHk65GKowCX6TUpDIw8C70PJx0JVJhFPgipabxQpjQqKtuJXIKfJFSU1MLLTdA94NBS18kIgp8kVKUaoNjB6Hn0aQrkQqiwBcpRXMuhvpTdScsiZQCX6QU1TZA83XQ/QAMHk26GqkQCnyRUpVqgyP7YM9Pkq5EKoQCX6RUNV0BtZM1Wkcio8AXKVV1k2HeYti5Bnww6WqkAijwRUpZKgPvvgF7f5Z0JVIBFPgipaz5GqhpULeOREKBL1LK6qfB3MuD4ZkldO8KKU8KfJFSl8rAO53w5i+SrkTKXKG3OPwtM3vRzAbNLJ21fIGZHTKzTeHjzsJLFalSLUug6WrQXUKlQHUFfn4zkAH+Ice6be6+sMD9i8iEmXDxuqSrkApQUOC7+xYAM4umGhERiU2cffinm9kvzOwnZvaJGI8jIiJjMGoL38weA+bmWLXC3e8f4WM9QKu795nZh4D7zOw8d387x/6XA8sBWltbx165iIiMy6iB7+6XjXen7n4YOBy+3mhm24CzgI4c264CVgGk02mNOxMRiUksXTpm1mhmteHrM4AzgdfiOJaIiIxNocMyl5pZF/Ax4CEzWx+uugh43syeA/4D+H1331dYqSIiUohCR+msAdbkWH4voDs3iIiUEF1pKyJSJcxLaH4OM+sFOkfZbBawtwjlFJPOqTzonMpDNZ7TfHdvHG0nJRX4Y2FmHe6eHn3L8qFzKg86p/KgcxqZunRERKqEAl9EpEqUY+CvSrqAGOicyoPOqTzonEZQdn34IiKSn3Js4YuISB7KIvDN7Mtm9nx4M5VHzGxeuNzM7JtmtjVcf0HStY6Vmf2Vmb0U1r3GzKZnrftieE4vm9mVSdY5HiPdECdcV5bnBGBmV4V1bzWz25OuJ19mdreZ7TGzzVnLTjOzR83s1fB5RpI1joeZpczsCTPbEv7c3RYuL+dzmmhmz5rZc+E5/Wm4/HQzeyY8p38zs4a8DuDuJf8ApmW9/gPgzvD1YuBhwICPAs8kXes4zukKoC58/RfAX4SvzwWeAyYApwPbgNqk6x3jOb0fOBv4MZDOWl7O51Qb1nsG0BCex7lJ15XnuVwEXABszlr2l8Dt4evbh34Oy+EBNAEXhK9PAV4Jf9bK+ZwMmBq+rgeeCbPtB8CN4fI7gc/ms/+yaOH7idMqTwGGvnhYAvyzB54GpptZU9ELzIO7P+Lux8K3TwMt4eslwPfd/bC7vw5sBRYlUeN4ufsWd385x6qyPSeCOre6+2vufgT4PsH5lB13fxIYPqfVEuCe8PU9wA1FLaoA7t7j7j8PXx8AtgDNlPc5ubsfDN/Whw8HLiGYlwwKOKeyCHwAM1tpZjuBm4A/CRc3AzuzNusKl5WbWwj+UoHKOads5XxO5Vz7WMxx9x4IAhSYnXA9eTGzBcD5BC3isj4nM6s1s03AHuBRgr8w38pqIOb9M1gygW9mj5nZ5hyPJQDuvsLdU0A7cOvQx3LsqmSGHY12TuE2K4BjBOcFFXBOuT6WY1nJnNMoyrn2qmBmUwkma/yC57jJUrlx9wEP7gfeQvAX5vtzbZbPvgu9iXlkfOw3WvlX4CHgSwS/6VJZ61qAXRGXlrfRzsnMlgHXApd62DlHmZ/TCEr6nEZRzrWPxW4za3L3nrA7dE/SBY2HmdUThH27u68OF5f1OQ1x97fM7McEffjTzawubOXn/TNYMi38kzGzM7PeXg+8FL5eC/yvcLTOR4H9Q3/KlTozuwr4f8D17t6ftWotcKOZTTCz0wluHvNsEjVGqJzPaQNwZjhKogG4keB8KsVaYFn4ehkw0m1LS46ZGXAXsMXdv5a1qpzPqXFoxJ6ZTQIuI/hu4gngU+Fm+Z9T0t9Kj/Gb63uBzcDzwANAc9Y32t8i6ON6gayRIaX+IPjiciewKXzcmbVuRXhOLwNXJ13rOM5pKUGL+DCwG1hf7ucU1r6YYATINoJ7OSdeU57n8T2C+00fDf+dfg+YCTwOvBo+n5Z0neM4nwsJujaez/p/tLjMz+mDwC/Cc9oM/Em4/AyCRtJW4N+BCfnsX1faiohUibLo0hERkcIp8EVEqoQCX0SkSijwRUSqhAJfRKRKKPBFRKqEAl9EpEoo8EVEqsR/A4IUcMBnje6uAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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K/U5bd38MeCzs/Yj03yGVebr4wMnzIzVlSs7FmfH4v/vKVezZN4kv/v6dtH70IgBaW+HgwaPr1tbCHXeUphyRkVJrBYmPpUuPhv0oaWmBlpZx8EILC0/8V7hmD9RO7i9n8+ZgWueyZbpgK9FTawWpbNlDOKU6ox+opyf/Oqk26DsAm74H0H+Rt68v+K2wl3KgwJfKlRnCyUypDEtV1XFz848z5dzg6VQbi+uTLxImBb5UrtEawjlyJJib/7ncnTH7NbXCnpeg56XwaxIZAQW+VK5BZs+Ewh2+852hz/TntkDVWOhcMXp1iQyDAl8q12BNbsLiHnyrGEztZJh9DWxqhyMfjF5dIgVS4EvlGqzJTZjyfatItcLBPbDl4dGpR2QYFPhSubKb3GSeKFLIMweLke9bxfT/ARMaoFMXb6X8KPClsg2c/ximQnobWxU0LYa3n4b3Q65HZJgU+BIv+/aVdnt1dcN/HmHTzYBB56rS1iJSJAW+SC5mcOutsGvX8O+emtAAp1wMnSvB+0ItU2Q4FPgSLyPtUGYGEycePZu/+2741rdGXkeqDXo3w9urR74NkRJT4Eu83HEH1IygRZR7cCZ/992l6YUwayHUTtGdt1JWFPgSLy0tcPLJI/vb3t6h59kPR/U4aGyBrQ/DgQJ68YiMAgW+xE8hzc4GU8oGbKnWYxqqiURNgS/xU+wduBdfPORDzQs2+RyY/DHNyZeyocCX+Cn2DtzVq499qHn6ubYjkmqFPS9Dz4sjr0ekRBT4Ek/jxx99XVcXPHn8nntGNounmLH9xhuDhmob1VBNoqfAl3jJ9Mjfvfvosv37g98tLcG8evfgp2oY//uPtDOnGqpJGVHgS7zk6pGf6wx9uEM0xVwXSLXBoXdgy0Mj34ZICSjwJV4GOxMfuHzp0mDefSEK6aEzlOkXwoRGzcmXyCnwJV4GOxMfuHw4QzSF9tAZTKah2o7VaqgmkVLgS7zkmqGT6wy90CGahobSPIG8v6HayuK3JTJCoQW+mf2tmW0zs5fTP5eHtS+Rfrl65Oc6Qy9k6maxQznZJsyBGZcGgd93pDTbFBmmsM/wv+7u56R/Hgt5XyKBgT3yc52h5/qH4dZb8/9DUYymVujdEgztiERgBF2mRGKipaW0gZ5PdkO1GZeO3n5F0sI+w/+Cmb1iZivMbHLI+xIpb9VjofGz6YZqu/OvL1JiRQW+mT1tZuty/CwEvg2kgHOA7cDtg2xjiZl1mFlHd3d3MeWIlL9UK/QdDG7EEhll5u7h78SsEfihu5811HrNzc3e0dERej0ikfpxM/QdgsteDq4XiBTJzNa6e3O+9cKcpTMj6+3VwLqw9iVSUZpa4Z1XYI8aqsnoCnMM/3+b2atm9gpwIfBnIe5LpHI03hg8IEUN1WSUhTZLx91vCmvbIhWtdhLMvjYYxz/3n6BmfP6/ESkB3WkrEoVUGxx6F7Y8GHUlkiAKfJEoTPsUTJgLnRrWkdGjwBeJglUFUzR3/ATe74y6GkkIBb5IVOYuImiotirqSiQhFPgiUZkwWw3VZFQp8EWilGqD3q3w9tNRVyIJoMAXidLMK2FsHXTqaVgSPgW+SJSyG6p9sCvqaiTmFPgiUUu1Bb111FBNQqbAF4napI/AlOZgWGcUmhlKcinwRcpBqg3eeRV61kZdicSYAl+kHDRcn26opou3Eh4Fvkg5qJ0Esz8NXd+Dw71RVyMxpcAXKRepVji0Vw3VJDQKfJFyMe1TMLFJDdUkNAp8kXJhVdC0GHb8VA3VJBQKfJFy0nRzEPwbV0ZdicSQAl+knJwwC06ZD2+uUkM1KTkFvki56W+o9lTUlUjMKPBFys3M/wljp2pOvpScAl+k3FTXQuNNsO0R+KA76mokRhT4IuUo1aqGalJyCnyRcjTpLKibFwzrqKGalEhRgW9m15nZa2bWZ2bNAz67zcw2mNnrZja/uDJFEqipFd5dBz0dUVciMVHsGf464BpgTfZCMzsDuB44E1gAfMvMqovcl0iyNFwP1eN18VZKpqjAd/f17v56jo8WAve5+wF3fxPYAMwrZl8iiVN7crqh2r1qqCYlEdYY/kxgS9b7rellIjIcqbZ0Q7UHoq5EYiBv4JvZ02a2LsfPwqH+LMeynFeezGyJmXWYWUd3t6agiRxj2vkwMQUb1VBNileTbwV3v3gE290KzM56Pwt4a5DtLweWAzQ3N2s6gkg2s2CK5i+Wwnsb4cRU1BVJBQtrSOdR4HozG2tmc4HTgedD2pdIvM1dFDRU61RDNSlOsdMyrzazrcAngB+Z2RMA7v4acD/wS+DHwOfdXZ2gREbihJkwYwF0rlJDNSlKsbN0HnL3We4+1t2nu/v8rM+WuXvK3T/s7o8XX6pIgjW1wv5tsP2JqCuRCqY7bUUqQaahWqfm5MvIKfBFKkF/Q7UfqKGajJgCX6RSpNrSDdXuiboSqVAKfJFKMelMqPttNVSTEVPgi1SSVCu8+xrs1ixnGT4FvkglyTRU69SdtzJ8CnyRSjLmJJhzHWxSQzUZPgW+SKVJtcHh92Dz96OuRCqMAl+k0tR/Eiaepjn5MmwKfJFKk2motnMN7H0j6mqkgijwRSrR3D8MGqq9uSrqSqSCKPBFKtEJM2HGZemGaoejrkYqhAJfpFKlWmH/W7D9yagrkQqhwBepVKdeAadeHvTZESlA3ideiUiZqq6FC34UdRVSQXSGLyKSEAp8EZGEUOCLiCSEAl9EJCEU+CIiCaHAFxFJCAW+iEhCKPBFRBLCvIyejWlm3UBX1HXkMRXYFXUREUnysUOyj1/HXt4a3L0+30plFfiVwMw63L056jqikORjh2Qfv449HseuIR0RkYRQ4IuIJIQCf/iWR11AhJJ87JDs49exx4DG8EVEEkJn+CIiCaHAL4CZ/aOZ/crMXjGzh8xsUtZnt5nZBjN73czmR1lnWMzsOjN7zcz6zKx5wGdJOP4F6ePbYGZfjrqesJnZCjPbaWbrspZNMbOnzOyN9O/JUdYYFjObbWY/NbP16f/n/yS9PBbHr8AvzFPAWe7+UeDXwG0AZnYGcD1wJrAA+JaZVUdWZXjWAdcAa7IXJuH408fzTeAy4AzghvRxx9kqgv+e2b4MrHb304HV6fdxdBj4c3f/TeB3gM+n/3vH4vgV+AVw9yfdPfOk6OeAWenXC4H73P2Au78JbADmRVFjmNx9vbu/nuOjJBz/PGCDu3e6+0HgPoLjji13XwP0DFi8ELgr/fou4KpRLWqUuPt2d38x/fo9YD0wk5gcvwJ/+FqBx9OvZwJbsj7bml6WFEk4/iQcYyGmu/t2CEIRmBZxPaEzs0bgXOC/iMnx65m2aWb2NHBKjo+Wuvsj6XWWEnzla8/8WY71K3LaUyHHn+vPciyryOMfQhKOUQYws4nAA8Cfuvtes1z/G1QeBX6au1881Odmtgi4ArjIj85l3QrMzlptFvBWOBWGK9/xDyI2xz+EJBxjIXaY2Qx3325mM4CdURcUFjMbQxD27e7+YHpxLI5fQzoFMLMFwF8DV7p7b9ZHjwLXm9lYM5sLnA48H0WNEUnC8b8AnG5mc82sluAi9aMR1xSFR4FF6deLgMG+9VU0C07l7wTWu/v/yfooFsevG68KYGYbgLHA7vSi59z9f6U/W0owrn+Y4Ovf47m3UrnM7GrgG0A98A7wsrvPT3+WhOO/HPi/QDWwwt2XRVxSqMzsXuACgi6RO4CvAA8D9wNzgM3Ade4+8MJuxTOz3wN+DrwK9KUX/w3BOH7FH78CX0QkITSkIyKSEAp8EZGEUOCLiCSEAl9EJCEU+CIiCaHAFxFJCAW+iEhCKPBFRBLivwH+lIeu46kj5gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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5cQK+973QfiuRXoUd+FuBiZ2+nwBs7/wC59xy51y9c66+srIy5HIkcbrevafTp6883nUMBoLt3awzeDL8OzqMn/4uzUU1r3NJ7Ys5ldPdjB2RQgg78F8BUmY22cwGAbOBJ0I+p0hg9erT796XLs195fEc1hm8YEYDB46ccUp/nUGDBlK0SHhCDXznXBvwXeAXwLvAw865t8M8pyRY17v5BQuy3733RUtLj7tvbBjOjiHzmHXJzxg7YhfV1bBiRfCANpvutosUQujz8J1zTzvn6pxzU51zmogm4Tj5dtjOd/OHDuXv2D341LVpBpcdZ+dvVnz8QPaHPzz9Tn/QoGC7iC/qpSPFoevbYfN97J6M+AyMuxyal0FHOxCE/ooVwcPdk1MxV6zQ7BzxS4Ev8dR1+KaXoZcB6fpW22xSaTjUAtuf/njTJw93NRVTokGBL/GTbfgmzGbyJSW9DuswYQYMPQealoRXh8gAKfAlfrIN3zgXXui3t8NNNwVTOrtTUg6182HHM/DR+nDqEBkgBb7ET3dDLM7BsGHhnNM5WLas5zv9qbeDlQZj+SIRpMCX+OmuzeTo0eE9uIUg9Ht6gFtxDkyYCetXQNuR8OoQ6ScFvsRPtm5mFRVw9Gj3y0/lS28PcOvScHwvbP5puHWI9IMCX+Knczezk3Me583L37z7nvTWxH7sZXDmp6Fpafi1iPSRAl/iqeucx6ef7u0nBi6XJvZmwRTNPS/DnsbwaxLpAwW+FIdc5sr3R+e/InJtYj/521A2TFM0JXK0pq0Uh0mT8v/mq9Gjg78e+mrQCKiZCxtXwkX/CINH5bcukX7SHb4Uh3yvF1hePrDGN6mF0H4UNtyft5JEBkqBL8WhoaH/rSirq2HhwlOHb+67b2C9EEZeAJVfCB7euo7+H0ckjxT4Ujz6e0fe0gIrVwZ/JeSz8U1qERxshh3PDvxYInmgwJfi0dDQ/3fa5rDYSZ9NvAGGjIWmu3t/rUgBKPCluAzknbb5fuhbOhim3gbbnwo6aYp4psCX4tLbG6N6k06f2na5ty6ZvaldEHxuXj6w44jkgQJfiku2tgt9sXTpqW2Xu1nIPGfDJsH462D9PdB+rP/HEckDBb4Ul2xtF07OwAEoLe3b8fIxtp9Kw9FdsOWRgR1HZIAU+FI8Tq6CddNNwferVgUzbpYsCT47B21tfW+wNtB38Z59JQyv1TtvxTsFvhSHbKtg9TQc05c5+wN9LmAlwRuxWn8DH74xsGOJDIACX4pDtlWwehqO+da3cjtuLg3TcjHlO1A6RF00xSsFvhSH7oZdutueS3fN0tLcG6b1ZvAoqJ4DG1fB8f0DP55IPyjwpTh0N+zS3fZcxuU7OvIT9ifVLYL2w7DxJ/k7pkgfKPClOHS3ClZ3wzG5jMsPdOy+q1EXw+hpwcPbsFfmEskitMA3s78ws21m9nrm4+thnUsk63TMnoZjepuvn6+x+65SaTjwHuz6Vf6PLdKLsO/wf+CcuzDzUYAliSTRuq6C1dNwTNd/IEaPDj76uthJX1XfCINHwzr115HC0wIoklwNDeGEek9Kh8CUW+C9f4bD26BifGHPL4kW9h3+d83sTTNbYWYjQz6XSDzULgh65Df/2HclkjADCnwze87M1mb5mAEsBaYCFwI7gH/q5hjzzazRzBpbW1sHUo5IPJwxFaqmw/rl0HHCdzWSIOYKMFvAzGqAJ51z5/X0uvr6etfY2Bh6PSLebXsS/v06uPRhmDTLdzUSc2b2qnOuvrfXhTlLp6rTtzOBtWGdSyR2qq6GYTV6560UVJhj+H9vZm+Z2ZvA5cCfhHgukXgpKYXUHbDzBdj/ju9qJCFCC3zn3E3Ouf/inDvfOXe9c25HWOcSiaUpt0DJIN3lS8HonbYivgyphEnfgg0r4cRB39VIAijwRXyqWwRtH8GmAS6lKJIDBb6IT6N/H0ZepP46UhAKfBGfzIL+OvveDBZIEQmRAl/Et5o5UD4CmtRfR8KlwBfxrWxYsCLWlkfgyE7f1UgRU+CLREFqYdBmYcO9viuRIqbAF4mCMz8F466ApmXQ0e67GilSCnyRqKhLw+EtsP1J35VIkVLgi0TF+Oth6HhYt8R3JVKkFPgiUVFSFvTK/+CXcKDJdzVShBT4IlFSextYmfrrSCgU+CJRMrQKJn4TNtwHbYd9VyNFRoEvEjV1aTixD1oe8l2JFBkFvkjUVH4RRnwW1t2t/jqSVwp8kag52V/nw9dgzyu+q5EiosAXiaLJc6FsuPrrSF4p8EWiqPxMmHwTtPwUju72XY0UCQW+SFSl0tBxLJixI5IHCnyRqDrrPBj7pWBOvuvwXY0UAQW+SJSl0nBoI2x/xnclUgQU+CJRNmEmDDk7WAJRZIAU+CJRVjoIam+H7U/DwY2+q5GYU+CLRF3tfLASaP6R70ok5hT4IlFXMSFonbz+Hmg/6rsaibEBBb6ZzTKzt82sw8zqu+z7vpk1m9n7ZnbVwMoUSbi6NBzbA5t/5rsSibGB3uGvBW4A1nTeaGbnArOBzwLTgSVmVjrAc4kk17ivwBl1WhxFBmRAge+ce9c5936WXTOAh5xzx5xzG4FmYNpAziWSaFYSTNHc8yLsfc13NRJTYY3hjwe2dPp+a2abiPTXlHlQOlRTNKXfeg18M3vOzNZm+ZjR049l2Za1z6uZzTezRjNrbG1tzbVukeQZdBbUNMCmf4Xj+3xXIzHUa+A75650zp2X5ePxHn5sKzCx0/cTgO3dHH+5c67eOVdfWVnZt+pFkqZuEbQfgQ0rfVciMRTWkM4TwGwzG2xmk4EU8HJI5xJJjpEXwpg/CIZ11F9H+mig0zJnmtlW4A+Ap8zsFwDOubeBh4F3gGeARc659oEWKyIED28/WgcfPO+7EokZcxFaQq2+vt41Njb6LkMk2tqPwmMTg6UQv/Rz39VIBJjZq865+t5ep3faisRN6RCYeitsexwOb/VdjcSIAl8kjmoXBAucNy/3XYnEiAJfJI6GT4ZzrgkCv/2472okJhT4InFVl4ajO2HrY74rkZhQ4IvEVdVVMGwyNN3tuxKJCQW+SFxZCaQWwq41sG+t72okBhT4InE25WYoGaz+OpITBb5InA0ZA9WzYeMqOHHAdzUScQp8kbhLpaHtIGx8wHclEnEKfJG4G/05GHVxpr9OdN45L9GjwBeJO7PgLn//29D6a9/VSIQp8EWKQfXsYJpm1qUoRAJlvgsQkTwoq4DLn/FdhUSc7vBFRBJCgS8ikhAKfBGRhFDgi4gkhAJfRCQhFPgiIgmhwBcRSQgFvohIQpiLUO8NM2sFWjydfgyw29O5o0jX43S6JqfS9TiVz+tR7Zyr7O1FkQp8n8ys0TlX77uOqND1OJ2uyal0PU4Vh+uhIR0RkYRQ4IuIJIQC/xPLfRcQMboep9M1OZWux6kifz00hi8ikhC6wxcRSYjEB76Z/YOZvWdmb5rZo2Z2Vqd93zezZjN738yu8llnoZjZLDN728w6zKy+y77EXQ8AM5ue+Z2bzexO3/X4YGYrzGyXma3ttG2UmT1rZk2ZzyN91lhIZjbRzF4ws3cz/3/5XmZ7pK9J4gMfeBY4zzl3PrAO+D6AmZ0LzAY+C0wHlphZqbcqC2ctcAOwpvPGpF6PzO94N3A1cC4wJ3MtkuZ+gv/dO7sTeN45lwKez3yfFG3AnzrnPgNcAizK/HcR6WuS+MB3zv3SOdeW+fZFYELm6xnAQ865Y865jUAzMM1HjYXknHvXOfd+ll2JvB4Ev2Ozc26Dc+448BDBtUgU59waYG+XzTOAlZmvVwLfKGhRHjnndjjnXst8/RHwLjCeiF+TxAd+F7cA/5b5ejywpdO+rZltSZXU65HU3zsX45xzOyAIQGCs53q8MLMa4CLgJSJ+TRKxpq2ZPQecnWXXYufc45nXLCb4M231yR/L8vqimNKUy/XI9mNZthXF9ehFUn9vyYGZDQceAf7YOXfALNqLyCci8J1zV/a038zmAdcCV7hP5qluBSZ2etkEYHs4FRZWb9ejG0V7PXqR1N87FzvNrMo5t8PMqoBdvgsqJDMrJwj71c65n2c2R/qaJH5Ix8ymA/8duN45d7jTrieA2WY22MwmAyngZR81RkRSr8crQMrMJpvZIIIH1094rikqngDmZb6eB3T312HRseBW/l7gXefcP3faFelrkvg3XplZMzAY2JPZ9KJz7o7MvsUE4/ptBH+y/Vv2oxQPM5sJ/G+gEtgHvO6cuyqzL3HXA8DMvg78C1AKrHDO3eW5pIIzsweBywg6Qu4E/hx4DHgYmARsBmY557o+2C1KZnYp8GvgLaAjs/l/EIzjR/aaJD7wRUSSIvFDOiIiSaHAFxFJCAW+iEhCKPBFRBJCgS8ikhAKfBGRhFDgi4gkhAJfRCQh/hNHGeZPiG3fGQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, y = generate_data(50)\n",
    "gradient_descent(X, y, 0.2, 25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stochastic Gradient Descent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "def stochastic_gradient_descent(X, y, eta, T):\n",
    "    #T iterations\n",
    "    nmb_data = X.shape[0]\n",
    "    w = np.array([-2,-1,-3])\n",
    "    plot_scatter(X, y, w)\n",
    "    # your code here\n",
    "    for i in range(T):\n",
    "        loss = 0\n",
    "        for t in range(nmb_data):\n",
    "            loss += loss_i(w,X[i],y[i])\n",
    "            w = w-eta*grad_loss_i(w,X[i],y[i])\n",
    "        loss *= 0.5\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Applications/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:2: RuntimeWarning: covariance is not symmetric positive-semidefinite.\n",
      "  \n",
      "/Applications/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:3: RuntimeWarning: covariance is not symmetric positive-semidefinite.\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# generate data\n",
    "X, y = generate_data()\n",
    "stochastic_gradient_descent(X, y, 0.5, 15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
